基于S波段双偏振雷达资料的降水粒子类型识别算法及应用
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国家自然科学基金资助项目(42075077);国家重点研发计划重点专项(2018YFC1507604)


Hydrometeors classification and its application based on S-band dual polarization radar data
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    摘要:

    基于质量控制的S波段双偏振雷达格点化观测数据,利用模糊逻辑算法,结合降雨粒子散射和空间取向等特征建立了降水粒子类型识别算法,用于分析降水过程中降水粒子的空间分布情况及粒子类型的演变过程。该算法可以将降水粒子分为液态、冰态、混合态等不同种类,有助于发现影响降水多寡的云微物理关键结构。首先根据不同降水粒子的雷达回波特性得到隶属函数,其次根据不同雷达观测变量在判别粒子类型时的贡献不同,确定每个观测值对应的隶属函数值的权重,对各个函数值进行加权平均后,得到不同粒子类型对应的逻辑值。最后进行集成和退模糊化处理,选出每个格点中逻辑值的最大值,认为该值所代表的粒子类型即为该格点所代表的粒子类型。在确定观测值对应的隶属函数值的权重时,水平反射率因子和环境温度作为计算粒子类型的直接影响因子,不再进行加权平均计算,提出了基于S波段双偏振雷达参量和环境温度的降水粒子类型识别算法。通过华南前汛期一次降水过程,利用雷达观测降水资料,验证了该算法的合理性。验证结果表明,反演所得的“雨”类型的分布特征与实际观测降水的分布特征基本一致,证明该算法可以反映降水区域的粒子类型,识别结果基本合理。进一步研究发现在降水发生之前,空中存在大量“毛毛雨”类型的粒子,在降水发生时毛毛雨和雨粒子的变化呈负相关性,表明此次降水主要由毛毛雨碰并产生雨粒子并降落地面产生。

    Abstract:

    In this study,based on the quality-controlled S-band dual-polarization radar gridded observation data,a hydrometeors classification recognition algorithm is established,so as to analyze the spatial distribution and evolution of hydrometeors in the precipitation process by using the fuzzy logic algorithm,as well as the characteristics of hydrometeors scattering and spatial orientation.This algorithm can classify hydrometeors into different types such as liquid,ice,and mixed states,which is helpful in finding the key structures of cloud microphysics which affect the precipitation.First,the membership function is obtained according to the radar echo characteristics of hydrometeors.Second,according to the different contributions of radar observation variables in identifying hydrometeor types,the weight of the membership function value corresponding to each observation value is determined,and,after the weighted average of each function value is obtained,then the logical value corresponding to hydrometeors types is obtained as well.Finally,the integration and defuzzification processing is performed,and the maximum value of the logical value in each grid point is selected,after which the hydrometeor type represented by the value is considered to be the particle type represented by the grid point.When determining the weight of the membership function corresponding to the observed value,the horizontal reflectance factor and ambient temperature are taken as the direct influence factors for calculating the hydrometeor types,and,instead of the weighted average calculation,an algorithm for hydrometeor types recognition based on the parameters of S-band dual polarization radar and the ambient temperature is proposed.Next,the rationality of the algorithm is verified by means of a precipitation process in the pre-flood period of South China using radar and precipitation data.The study results show that the distribution characteristics of the rain-type obtained by the inversion are basically consistent with the distribution characteristics of the actual observed precipitation,which proves that the algorithm is able to reflect the hydrometeor types in the precipitation area,and that the recognition results are basically reasonable.Further research shows that there are a large number of drizzle-type particles present in the air before the occurrence of precipitation,and that there is a negative correlation between the changes of drizzle and rain particles during the process of precipitation,thereby indicating that this precipitation is mainly caused by the collision of drizzle and rain particles.

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宋文婷,李昀英,黄浩,朱科锋.2021.基于S波段双偏振雷达资料的降水粒子类型识别算法及应用【J】大气科学学报.44.2:209.218

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  • 收稿日期:2020-03-18
  • 最后修改日期:2020-08-07
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  • 在线发布日期: 2021-04-25
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